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Method and device for merging object detection information detected by each of object detectors

An object detection and integrated device technology, applied in optical observation devices, instruments, image communication, etc., can solve problems such as blind spots or occluded areas that cannot identify the actual situation, differences in information, and difficulty in ensuring various learning data.

Active Publication Date: 2020-08-04
STRADVISION
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  • Abstract
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AI Technical Summary

Problems solved by technology

[0006] However, since existing object detectors detect objects based on learned parameters, there is a disadvantage that it cannot be confirmed whether objects are detected accurately in real situations, and separate monitoring is required for this
[0007] Also, it is difficult for existing object detectors to secure various learning data for performance improvement
[0008] Moreover, the existing object detector system can only confirm the direction that the camera can see and the area that is not blocked by obstacles, so the system has the problem of not being able to recognize the actual situation for the blind spot or the blocked area
[0009] Also, existing object detectors can output different results according to the learned parameters, so there can be discrepancies between the information detected by the surrounding systems

Method used

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  • Method and device for merging object detection information detected by each of object detectors
  • Method and device for merging object detection information detected by each of object detectors
  • Method and device for merging object detection information detected by each of object detectors

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Embodiment Construction

[0048] In order to clarify the object, technical solution, and advantages of the present invention, the detailed description of the present invention to be described later refers to the accompanying drawings that show specific embodiments of the present invention as examples. These embodiments are described in detail so that those skilled in the art can sufficiently practice the present invention.

[0049]In addition, in the detailed description of the present invention and the protection scope of the invention claims, the term "comprising" and its variants are not intended to exclude other technical features, additives, components or steps. For those skilled in the art, some of the other objects, advantages, and features of the present invention are disclosed in this specification, and some are disclosed in practice of the present invention. The following examples and figures are provided as examples, but they are not intended to limit the invention.

[0050] In particular, ...

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Abstract

The invention provides a method for merging object detection information detected by object detectors by using auto labeling and evaluation based on information exchange (V2X) between a vehicle and the outside. Each of the object detectors corresponds to each camera nearby, and detects objects in each of images generated from each of the cameras by image analysis based on deep learning. The methodincludes steps of: if first to n-th pieces of object detection information are respectively acquired from a first to an n-th object detectors in a descending order of degrees of detection reliabilities, a merging device generating (k-1)-th object merging information by merging (k-2)-th objects and k-th objects through matching operations, and re-projecting the (k-1)-th object merging informationonto an image, by increasing k from 3 to n. The method can be used for a collaborative driving or an HD map update through V2X-enabled applications, sensor fusion via multiple vehicles, and the like.

Description

technical field [0001] The present invention relates to a method and apparatus for self-driving vehicles, and more particularly, to a method and apparatus for integrating object detection information detected by object detection corresponding to each camera located in the perimeter . Background technique [0002] Generally, deep learning (Deep learning) is defined as a collection of machine learning algorithms that try to achieve high-level abstraction through a combination of multiple nonlinear transformation techniques, and is a machine learning that enables computers to learn the way people think in a large framework. a field of . [0003] Expressing some data in a computer-readable form, as an example, expressing the pixel information of an image in the form of a column vector (column vector), and conducting various researches to apply it to machine learning, through these efforts, such as Various deep learning technologies such as deep neural network, convolutional ne...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04N7/18G06K9/00G06K9/62G08G1/0967G06V10/774
CPCH04N7/181G08G1/096725G06V20/52G06V10/751G06F18/241B60R2300/50B60R1/00H04W4/40G06V20/58G06V10/809G06V10/774G06F18/254G06T5/50G06T7/11G06T7/174G06T7/187G06T2207/20221G06V20/40G06T7/32G05D1/0276B60R2300/303G05D2201/0213G06T2207/30261G05D1/0246
Inventor 金桂贤金镕重金寅洙金鹤京南云铉夫硕焄成明哲吕东勋柳宇宙张泰雄郑景中诸泓模赵浩辰
Owner STRADVISION
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